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The utilisation of Artificial Intelligence (AI) applications in the energy sector is gaining momentum, with increasingly intensive search for suitable, high-quality and trustworthy solutions that displayed promising results in research. The growing interest comes from decision makers of both the industry and policy domains, searching for applications to increase companies’ profitability, raise efficiency and facilitate the energy transition. This paper aims to provide a novel three-dimensional (3D) indicator for AI applications in the energy sector, based on their respective maturity level, regulatory risks and potential benefits. Case studies are used to exemplify the application of the 3D indicator, showcasing how the developed framework can be used to filter promising AI applications eligible for governmental funding or business development. In addition, the 3D indicator is used to rank AI applications considering different stakeholder preferences (risk-avoidance, profit-seeking, balanced). These results allow AI applications to be better categorised in the face of rapidly emerging national and intergovernmental AI strategies and regulations that constrain the use of AI applications in critical infrastructures.
Michael Graetzel, Sandy Sanchez Alonso